Predicting Olive Tree Chlorophyll Fluorescence Using Explainable AI with Sentinel-2 Imagery in Mediterranean Environment by Leonardo Costanza, Beatriz Lorente, Francisco Pedrero Salcedo, Francesco Pasanisi, Vincenzo Giannico, Francesca Ardito, Carlota María Martí Martínez, Simone Pietro Garofalo

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Searching for New Integrals in the Euler–Poisson Equations by Alexander D. Bruno, Alexander B. Batkhin

“…In the classical problem of the motion of a rigid body around a fixed point, which is described by the Euler–Poisson equations, we propose a new method for computing cases of integrability: first, we provide algorithms for computing values of parameters ensuring potential integrability, and then we select cases of global integrability. …”
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The Value of PET/CT-Based Radiomics in Predicting Adrenal Metastases in Patients with Cancer by Qiujun He, Xiangxing Kong, Xiangxi Meng, Xiuling Shen, Nan Li

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Pinpointing the integration of artificial intelligence in liver cancer immune microenvironment by Ihtisham Bukhari, Ihtisham Bukhari, Mengxue Li, Guangyuan Li, Jixuan Xu, Pengyuan Zheng, Xiufeng Chu, Xiufeng Chu

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Nursing Educators’ Perspectives on the Integration of Artificial Intelligence Into Academic Settings by Moustaq Karim Khan Rony MSS, MPH, RN, Sumon Ahmad MPH, RN, Sabren Mukta Tanha MPH, RN, Dipak Chandra Das MSS, Mosammat Ruma Akter MSN, RN, Mst. Amena Khatun MPH, RN, Most. Hasina Begum MSN, RN, Md Ibrahim Khalil MSS, RN, Umme Rabeya Peu MSS, RN, Mst. Rina Parvin BSN, RN, Daifallah M Alrazeeni PhD, Fazila Akter MSc, RN

“…Background The integration of artificial intelligence (AI) into education has the potential to revolutionize teaching and learning practices, especially in nursing education, which combines theoretical and practical knowledge. …”
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A Novel Deeply-Learned Image Quality Analysis Algorithm for Clustering by Zhongzhe Chen, Xing Gao

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The prognostic predictive value of indirect bilirubin-inflammation score in patients with nasopharyngeal carcinoma by JI Huojin, LI Jun, LUO Yonglin, QIN Weiling, YE Yinxin, CAI Yonglin

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An algorithm to generate correlated input-parameters to be used in probabilistic sensitivity analyses by Mohamed Neine, Desmond Curran

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The impact of algorithm awareness training on competent interaction with intelligent voice assistants by André Markus, Maximilian Baumann, Jan Pfister, Andreas Hotho, Astrid Carolus, Carolin Wienrich

“…Abstract Intelligent Voice Assistants (IVAs) have become integral to many users' daily lives, using advanced algorithms to automate various tasks. …”
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Adaptive Synchronverter Algorithm Using Q-Learning for Microgrid Stability Control by Mohd Brado Frasetyo, Fransisco Danang Wijaya, Husni Rois Ali, Muhammad Zharfan Wiranata

“…The integration of renewable energy sources into microgrids often leads to stability challenges, primarily due to the absence of inertia typically provided by conventional generators. …”
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Enhancing Heart Disease Prediction with Federated Learning and Blockchain Integration by Yazan Otoum, Chaosheng Hu, Eyad Haj Said, Amiya Nayak

“…Horizontal federated learning was implemented using the federated averaging algorithm to securely aggregate model updates across participants. …”
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Improve the Hunger Games search algorithm to optimize the GoogleNet model. by Yanqiu Li, Shizheng Qu, Huan Liu

“…Firstly, adaptive weights and chaos mapping were integrated into the hunger search algorithm to construct a new algorithm, ATHGS. …”
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A Multi-Objective Hybrid Game Pricing Strategy for Integrated Energy Operator-Load Aggregator Alliances Considering Integrated Demand Response by Yunlong Wang, Shan He

“…This study aims to establish an alliance of integrated energy service providers and load integrators, which optimizes the operation of the integrated energy system and maximizes in order tothe interests of all participants through the collaborative operation mechanism of new Power to Gas (P2G) and Interruptible Demand Response (IDR). …”
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Student knowledge tracking based multi-indicator exercise recommendation algorithm by Bin ZHUGE, Zhenghu YIN, Wenxue SI, Lei YAN, Ligang DONG, Xian JIANG

“…Personalized exercise recommendation was an important topic in the era of education informatization, the forgetting laws of students in the learning process were ignored by the traditional problem recommendation algorithm, which failed to fully tap the students’ knowledge mastery level and the common characteristics of similar students, insufficient, could not reasonably promote students’ learning of new knowledge or help students find and fill omissions.In view of the above defects, a multi-index exercise recommendation method based on student knowledge tracking was proposed, which was divided into two modules: preliminary screening and re-filtering of exercises, focusing on the novelty, difficulty and diversity of exercise recommendation.Firstly, a knowledge probability prediction (SF-KCCP) model combined with students’ forgetting law was constructed to ensure the novelty of the recommended exercises.Then, students’ knowledge and concept mastery level was accurately excavated based on the dynamic key-value knowledge tracking (DKVMN) model to ensure that exercises of appropriate difficulty were recommended.Finally, the user-based collaborative filtering (UserCF) algorithm was integrated into the re-filtering module, and the similarity between student groups was used to achieve the diversity of recommendation results.The proposed method is demonstrated by extensive experiments to achieve better performance than some existing baseline models.…”
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Student knowledge tracking based multi-indicator exercise recommendation algorithm by Bin ZHUGE, Zhenghu YIN, Wenxue SI, Lei YAN, Ligang DONG, Xian JIANG

“…Personalized exercise recommendation was an important topic in the era of education informatization, the forgetting laws of students in the learning process were ignored by the traditional problem recommendation algorithm, which failed to fully tap the students’ knowledge mastery level and the common characteristics of similar students, insufficient, could not reasonably promote students’ learning of new knowledge or help students find and fill omissions.In view of the above defects, a multi-index exercise recommendation method based on student knowledge tracking was proposed, which was divided into two modules: preliminary screening and re-filtering of exercises, focusing on the novelty, difficulty and diversity of exercise recommendation.Firstly, a knowledge probability prediction (SF-KCCP) model combined with students’ forgetting law was constructed to ensure the novelty of the recommended exercises.Then, students’ knowledge and concept mastery level was accurately excavated based on the dynamic key-value knowledge tracking (DKVMN) model to ensure that exercises of appropriate difficulty were recommended.Finally, the user-based collaborative filtering (UserCF) algorithm was integrated into the re-filtering module, and the similarity between student groups was used to achieve the diversity of recommendation results.The proposed method is demonstrated by extensive experiments to achieve better performance than some existing baseline models.…”
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Forecasting Renewable energy and electricity consumption using evolutionary hyperheuristic algorithm by Yang Cao, Jun Yu, Rui Zhong, Masaharu Munetomo

“…To address this, we propose an auto-evolution hyper-heuristic algorithm named AE-GAPB. AE-GAPB integrates a genetic algorithm (GA) at the high-level component and employs particle swarm optimization (PSO) and the bat algorithm (BA) at the low-level component. …”
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Segmentation of Stone Slab Cracks Based on an Improved YOLOv8 Algorithm by Qitao Tian, Runshu Peng, Fuzeng Wang

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Reputation-Based Leader Selection Consensus Algorithm with Rewards for Blockchain Technology by Munir Hussain, Amjad Mehmood, Muhammad Altaf Khan, Rabia Khan, Jaime Lloret

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Improved Grey Wolf Algorithm: A Method for UAV Path Planning by Xingyu Zhou, Guoqing Shi, Jiandong Zhang

“…Compared to Particle Swarm Optimization (PSO), Artificial Bee Colony (ABC), GWO, and MP–GWO algorithms, the NI–GWO algorithm can achieve the optimal fitness value and has significant advantages in terms of average path length, time, number of collisions, and obstacle avoidance capabilities.…”
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PID CONTROLLER FOR SPEED CONTROL OF PMSM BASED ON MAYFLY OPTIMIZATION ALGORITHM by Fatimah F. Jaber

“…Nuptial dancing and random flight improve the ability of the algorithm to balance its features of exploitation and exploration while assisting in its escape from local optima. …”
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